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We make our thinking on this subject clear with the use of a simple modeling framework, borrowed from the class of models known as pursuit-evasion games.
We propose a simple modeling framework with two components.
Because this is achieved with a simple modeling framework, one can investigate large networks with relatively sparse data compared to other formalisms for modeling of signaling networks [ 12, 17, 45, 46].
Thus the ITD model appears to be a relatively parsimonious model, reconciling different species-specific patterns of canopy structure, and crown size and shape, in a wide variety of forest communities, into a simple modeling framework.
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We employed a simple and flexible modeling framework to describe the relationship between co-localized TFs and target genes [ 24].
In doing so, we standardize a simple modeling approach and analytic framework in order to facilitate comparison.
For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required.
As several initial conditions may fall into the same attractor, we define the size of the basin of attraction B k as the number of initial conditions that fall into attractor K. Our extension of this traditional modeling framework consists in two simple modifications.
Furthermore, we tried to clarify in the manuscript that our modeling framework is not only a simple model of drive-reduction, but gives a normative computational theory for the interplay between the former and reinforcement learning theories of motivation.
Hence, in this paper, we propose a modeling framework that allows developers to model simple behavior-based robotic systems enhanced by the use of Central Pattern Generators (CPGs) for modulating the sensor-motor loops.
Given that both questions require modeling exercises that go beyond a simple Boolean GRN model, in this contribution we first propose a modeling framework to extend the Boolean FOS-GRN model to a continuous system, and then show how it can be used to explore the questions addressedhere.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com